Comparing the Language Abilities of Typically Developing and Dyslexic Children Aged 7 to 11 Using Quantitative Electroencephalography

Document Type : Research Paper

Authors

1 Department of Foreign languages and linguistics, school of literature and humanities, Shiraz University, Shiraz, Iran

2 Department of Psychology, psychology and Educational Science Faculty, Islamic Azad University of Marvdasht Branch, Fars, Iran

3 Department of Psychology, psychology and Educational Science Faculty, Islamic Azad University of Arsanjan Branch, Fars, Iran

Abstract

During an EEG eyes-opened state, the current investigation aimed to compare the language abilities of typically developing and dyslexic children. This research employed a descriptive-analytical design. The statistical sample for the study comprised 19 typical children residing in Shiraz city during the academic year 2020-2021 and 20 dyslexic children aged 7 to 11 who were referred to psychologists at the Mehraz Andisheh Clinic. The remaining 19 children were selected using the purposeful sampling method. The Wechsler Intelligence Scale for Children (WISC-IV) was utilized in the diagnostic process for children diagnosed with dyslexia. EEG data were quantified using Neuroguide software and analyzed using the Wilcoxon test in SPSS-23. The QEEG findings revealed that dyslexic children exhibited greater absolute power in the delta and theta regions of the frontal, parietal, left, and right hemispheres compared to the control group. However, the control group demonstrated greater absolute power in these areas in comparison to the dyslexics. The results corroborate the conclusions drawn in other studies and validate the presence of an atypical linguistic network among individuals with dyslexia. Thus, the investigation of brain waves may have a beneficial effect on the clinical treatment of individuals with dyslexia and can be utilized to better identify the language abilities of dyslexics.
 

Keywords


عابدی، م. ر.، صادقی، ا.، و ربیعی، م. (1394). هنجاریابی آزمون هوشی وکسلر کودکان چهار در استان چهارمحال و بختیاری. دست‌آوردهای روان‌شناختی (علوم تربیتی و روان‌شناسی). 22(2)، 116-99.
References
Abedi, M. R., Sadeghi, A., & Rabiei, M. (2015). Standardization of the Wechsler Intelligence Scale for children-IV in Chahar Mahal Va Bakhteyari State. Journal of Psychological Achievements (Journal of Education and Psychology), 22(2), 99-116. https://doi. 10.22055/psy.2016.12310 (In Persian)
Asaridou, S. S., Demir-Lira, O. E., Goldin-Meadow, S., & Small, S. L. (2017). The pace of vocabulary growth during preschool predicts cortical structure at school age. Neuropsychologia. 98, 13-23. https://doi.org/10.1016/j.neuropsychologia.2016.05.018
 Bartsch, F., Hamuni, G., Miskovic, V., Lang, P. J., & Keil, A. (2015). Oscillatory brain activity in the alpha range is modulated by the content of word-prompted mental imagery. Psychophisiology, 52(6), 727-735. https://doi.org/10.1111/psyp.12405
Beese, C., Meyer, L., Vassileiou, B., & Friederici, A. D. (2017). Temporally and spatially distinct theta oscillations dissociate a language-specific from a domain-general processing mechanism across the age trajectory. Scientific Reports, 7, 11202. https://doi.org/10.1038/s41598-017-11632-z
Berwick, R. C., Friederici, A. D., Chomsky, N., & Bolhuis, J. J. (2013). Evolution, brain, and
 the nature of language. Trends in Cognitive Sciences, 17(2), 89–98. https://doi.org/10.1016/j.tics.2012.12.002
Cornoldi, C., Orsini, A., Cianci, L., Giofre, D., & Pezzuti, L. (2013). Intelligence and working memory control: evidence from the WISC-IV administration to Italian children. Learning and Individual Differences, 26(1), 9-14.
D`Mello, A., & Gabrieli, D. E. (2018). Cognitive Neuroscience of Dyslexia. Language, Speech, and Hearing Services in Schools, 49(4), 798-809. https://doi.org/10.1044/2018_LSHSS-DYSLC-18-0020
De´monet, J. F., Taylor, M. J., & Chaix, Y. (2004). Developmental dyslexia. Lancet, 363(9419). 1451–1460. https://doi.org/10.1016/S0140-6736(04)16106-0
Ferré, P., Benhajali, Y., Steffener, J., Stern, Y., Joanette, Y., & Bellec, P. (2019). Resting-state and vocabulary tasks distinctively inform on age-related differences in the functional brain connectome. Language Cognition and Neuroscience, 34(8), 949-972. https://doi.org/10.1080/23273798.2019.1608072
Gaudet, I., Husser, A., Vannasing, Ph., & Gallagher, A. (2020). Functional brain connectivity
 of language functions in children revealed by EEG and MEG: A systematic review. Frontiers in Human Neuroscience, 14, 62. https://doi.org/10.3389/fnhum.2020.00062
Georgiewa, P., Rzanny, R., Gaser, C., Gerhard, U. J., Vieweg, U., Freesmeyer, D., ... & Blanz, B. (2002). Phonological processing in dyslexic children: A study combining functional imaging and event related potentials. Neuroscience Letters, 318(1), 5–8. https://doi.org/10.1016/s0304-3940(01)02236-4
Gudi-Mindermann, H., Rimmele, J.M., Bruns, P., Kloosterman, N.A., Donner, T.H., Engel, A.K. & Röder, B. (2020). Post-training load-related changes of auditory woking memory- An EEG study. Frontiers in Human Neuroscience. 14, 72. https://doi.org/10.3389/fnhum.2020.00072
Seshadri, N. G., & Singh, B. K. (2020, December). Hemispheric lateralization analysis in dyslexic and normal children using rest-EEG. In 2020 IEEE Recent Advances in Intelligent Computational Systems (RAICS) (pp. 37-41). IEEE. https://doi.org/10.1109/RAICS51191.2020.9332509
Longo, R. E. & Russo, G. M. (2017). Working with forensic populations: incorporating peripheral biofeedback and brainwave biofeedback into your organization or practice. In The F. Collura and J.A. Frederick (eds). Handbook of Clinical QEEG and Neurotherapy (pp. 92-105). New York: Routledge.
Marchand-Krynski, M. E., Morin-Moncet, O., Belanger, A. M., Beauchamp, H., & Leonard, G. (2017). Share and differentiated motor skill impairments in children with dyslexia and/or attention deficit disorder: From simple to complex sequential coordination. Plos One, 12(5), e0177490. https://doi.org/10.1371/journal.pone.0177490
Martinez-Briones, B., Fernandez-Harmony, T., Garofalo Gomez. N., Biscay-Lirio, R.J., & Bosch-Bayard, J. (2020). Working memory in children with learning disorders: An EEG power spectrum analysis. Brain Sciences, 10(11), 817. https://doi.org/10.3390/brainsci10110817
Middleton, A. E., Schneider, J. M., & Maguire, M. J. (2017). Age-related differences in beta engagement during single word processing. Language Cognition and Neuroscience, 32(10), 1250-1260. https://doi.org/10.1080/23273798.2017.1297841
Molinaro, N., Monsalve, I. F., & Lizarazu, M. (2016). Is there a common oscillatory brain mechanism for producing and predicting language? Language Cognition and Neuroscience, 31(1), 145-158. https://doi:10.1080/23273798.2015.1077978
Morgan, P. L., Farkas, G., Hillemeier, M. M., Hammer, C. S., & Maczuga, S. (2015). 24-month-old children with larger oral vocabularies display greater academic and behavioral functioning at kindergarten entry. Child Development, 86(5), 1351-1370. https://doi.org/10.1111/cdev.12398
Ortiz, T., Exposito, F.J., Miguel, F., Martin-Loeches, M. & Rubia, F. J. (1992). Brain mapping in dysphonemic dyslexia: in resting and phonemic discrimination conditions. Brain and Language, 42(3), 270-285. https://doi.org/10.1016/0093-934X(92)90101-J
Papagiannopoulou, E.A., & Lagopoulos, J. (2016). Resting state EEG hemispheric power asymmetry in children with dyslexia. Frontiers in Pediatrics, 4, 11. https://doi.org/10.3389/fped.2016.00011
Paus, T. (2005). Mapping brain maturation and cognitive development during adolescence. Trends in Cognitive Sciences, 9 (2), 60-68. https://doi.org/10.1016/j.tics.2004.12.008
Pavithran, G. P., Arunkumar, K., Guhan Seshadri, N.P., Singh, B.K., Mahesh, V., & Geethanjali, B. (2019). Index of Theta/Alpha ratio to quantify visual – Spatial attention in dyslexics using Electroencephalogram. 5th International Conference on Advanced Computing and Communication Systems (ICACCS). Coimbatore, India, 15-16 March 2019, pp. 417-422. https://doi.org/10.1109/ICACCS.2019.8728482
Penolazzi, B., Spironelli, CH., & Angrilli, A. (2008). Delta EEG activity as a marker of dysfunctional linguistic processing in developmental dyslexia. Psychophysiology, 45(6), 1025-1033. https://doi.org/10.1111/j.1469-8986.2008.00709.x
Peyrin, C., Démonet, J. F., N’Guyen-Morel, M. A., Le Bas, J. F., & Valdois, S. (2011). Superior parietal lobule dysfunction in a homogeneous group of dyslexic children with a visual attention span disorder. Brain and Language, 118(3), 128–138. https://doi.org/10.1016/j.bandl.2010.06.005
Poeppel, D., & Assaneo, M. F. (2020). Speech rhythms and their neural foundations. Nature Reviews Neuroscience, 21(6), 322-334. https://doi.org/10.1038/s41583-020-0304-4
Pugh, K. R., Mencl, W. E., Jenner, A. R., Katz, L., Frost, S. J., Lee, J. R., Shaywitz, S. E., & Shaywitz, B. A. (2000). Functional neuroimaging studies of reading and reading disability (Developmental dyslexia). Mental Retardation and Developmental Disabilities Research Reviews, 6(3), 207–213. https://doi.org/10.1002/1098-2779(2000)6:3<207::AID-MRDD8>3.0.CO;2-P
Raschle, N. M., Zuk, J., & Gaab, N. (2012) Functional characteristics of developmental dyslexia in left- hemispheric posterior brain regions predate reading onset. Proceedings of the National Academy of Sciences, 109(6), 2156–2161. https://doi.org/10.1073/pnas.1107721109
Rippon, G. & Brunswick, N. (2000). Trait and state EEG indices of information processing in developmental dyslexia. International Journal of Psychophysiology, 36(3), 251-265. https://doi.org/10.1016/s0167-8760(00)00075-1
Schiavone, G., Linkenkaer-Hansen, K., Maurits, N. M., Plakas, A., Maassen, B. A., Mansvelder, H. D., ... & van Zuijen, T. L. (2014). Preliteracy signatures of poor-reading abilities in resting- state EEG. Frontiers in Human Neuroscience, 8, 735. https://doi.org/10.3389/fnhum.2014.00735
Shaywitz, S. E., & Shaywitz, B. A. (2008). Paying attention to reading: The neurobiology of reading and dyslexia. Developmental Psychopathology, 20(4), 1329–1349. https://doi.org/10.1017/S0954579408000631
Simos, P.G., Fletcher, J.M., Bergman, E., Breier, J.I., Foorman, B.R., Castillo, E.M., et al. (2002). Dyslexia-specific brain activation profile becomes normal following successful remedial training. Neurology, 58(8), 1203–1213. https://doi.org/10.1212/wnl.58.8.1203
Sowell, E. R., Thompson, P. M., Leonard, C. M., Welcome, S. E., Kan, E., & Toga, A. W. (2004). Longitudinal mapping of cortical thickness and brain growth in normal children. Journal of Neuroscience, 24(38), 8223-8231. https://doi.org/10.1523/JNEUROSCI.1798-04.2004
Temple, E., Poldrack, R. A., Salidis, J., Deutsch, G. K., Tallal, P., Merzenich, M. M., & Gabrieli, J. D. E. (2001). Disrupted neural responses to phonological and orthographic processing in dyslexic children: An fMRI study. Neuroreport, 12(2), 299–307. https://doi.org/10.1097/00001756-200102120-00024
Tuladhar, A. M., terHuurne, N., Schoffelen, J.-M., Maris, E., Oostenveld, R., & Jensen,O. (2007). Parieto-Occipital sources account for the increase in alpha activity with working memory load. Human Brain Mapping, 28(8), 785–792. https://doi.org/10.1002/hbm.20306
Wang, J., Wang, X., Wang, X., Zhang, H., Zhou, Y., Chen, L., Li, Y., et al. (2020). Increased EEG coherence and short-distance connectivity in children with autism spectrum disorders. Brain and Behavior, 10(10), e01796. https://doi.org/10.1002/brb3.1796
Whedon, M., Perry, N. B., & Bell, M. A. (2020). Relations between frontal EEG maturation and inhibitory control in preschool in the prediction of children's early academic skills. Brain and Cognition, 146, 105636. https://doi.org/10.1016/j.bandc.2020.105636
Xu, M., Yang, J., Siok, W. T., & Ting L. H. (2015). Atypical lateralization of phonological working memory in developmental dyslexia. Journal of Neurolinguistics, 33, 67–77. https://doi.org/10.1016/j.jneuroling.2014.07.004